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T0 review · glm-5.2

SKA can resolve disk winds and distinguish wind mechanisms

2026-07-09 06:34 UTC pith:5IGKTWXD

load-bearing objection Solid SKA feasibility study; the MHD density contrast does real work but the paper is honest about it the 3 major comments →

arxiv 2607.07571 v1 pith:5IGKTWXD submitted 2026-07-08 astro-ph.SR astro-ph.EPastro-ph.IM

Ionized gas emission in protoplanetary disks with the SKAO

Greta Guidi , Christian Rab , Barbara Ercolano , Michael L. Weber , Claudio Codella , Izaskun Jim\'enez-Serra , Evgenia Koumpia , John D. Ilee
show 15 more authors
Enrique Mac\'ias Elena Viscardi Yinhao Wu Francesca Bacciotti Asmita Bhandare Eleonora Bianchi Tyler Bourke Luca Cacciapuoti Antonio Garufi Geoffroy Lesur Vincent Pi\'etu Linda Podio Giovanni Sabatini Leonardo Testi Claudia Toci
This is my paper
classification astro-ph.SR astro-ph.EPastro-ph.IM
keywords diskdisksevolutionformationionizedprotoplanetarywindscomponent
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper asks whether the upcoming SKA-Mid telescope, in its full AA4 configuration, can detect and spatially resolve the ionized gas component of protoplanetary disk winds at nearby star-forming distances (140 pc). The authors simulate free-free continuum emission and hydrogen radio recombination lines from three classes of wind models—pure photoevaporative, magneto-thermal, and magnetohydrodynamic—and generate synthetic SKA observations to test detectability. The central claim is that SKA-Mid can spatially resolve free-free emission from disk winds with roughly 10 hours of integration (peak signal-to-noise of 4–13 depending on band and inclination), and that stacking the twelve hydrogen recombination lines within Band 5b yields spectrally resolved detections for all tested wind models at similar integration times (peak SNR of 6–31). The paper further argues that the line profiles and continuum spectral slopes differ enough between thermally driven and magnetically driven winds that SKA observations could distinguish the dominant wind-launching mechanism, with magnetically driven winds producing faster, denser, and more compact emission.

Core claim

The paper's central result is a feasibility demonstration: synthetic observations show that SKA-Mid AA4 can both spatially resolve free-free continuum emission from protoplanetary disk winds at 140 pc and spectrally resolve stacked hydrogen recombination lines in Band 5b with approximately 10 hours of integration. The discriminant power between wind mechanisms comes from two observables: the free-free spectral index, which is steeper (approximately 1.97, fully optically thick) for magneto-thermal winds versus shallower (approximately 1.13, partially optically thick) for photoevaporative winds, and the recombination line widths, which are broader for magnetically driven winds (FWHM up to 110+

What carries the argument

The central objects are synthetic SKA-Mid observations of free-free continuum emission and hydrogen radio recombination lines (Hα at cm wavelengths), generated by post-processing three classes of disk wind simulations: photoevaporative (PE), magneto-thermal (MT), and magnetohydrodynamic (MHD). The discriminant between wind mechanisms is the combination of continuum spectral slope and recombination line profile shape.

Load-bearing premise

The synthetic observations rely on wind models that are not directly comparable to each other: they cover different radial ranges, use different disk surface density profiles, and the MHD model assumes an isothermal disk independent of stellar properties. The claim that SKA can distinguish wind mechanisms depends on these models faithfully representing the density and velocity structure of real winds.

What would settle it

If real protoplanetary disk winds at 140 pc produce free-free emission below the predicted flux levels, or if recombination line profiles from photoevaporative and MHD winds are more similar than the models suggest (e.g., due to Keplerian broadening washing out wind-velocity differences at moderate inclinations), SKA observations would not cleanly distinguish the mechanisms.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • If SKA achieves the predicted sensitivity, it would provide the first systematic survey of ionized gas in protoplanetary disks at cm wavelengths, accessing a wind component that optical/IR observations probe only indirectly.
  • The ability to distinguish photoevaporative from MHD winds via line profiles would constrain the relative contributions of thermal versus magnetic disk dispersal mechanisms, which is currently a major open question in disk evolution theory.
  • A Band 5b survey of a star-forming region like Ophiuchus could be completed in approximately 60 pointings, making population-level studies of disk wind incidence feasible.
  • Multi-epoch observations could separate variable non-thermal (gyrosynchrotron) emission from steady free-free emission, isolating the wind signal.
  • Combined with JWST infrared spectroscopy and GRAVITY+ near-IR interferometry, SKA would bridge spatial scales from sub-au wind-launching regions to tens-of-au extended outflows.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The claim that line profiles distinguish wind mechanisms depends on the wind models accurately representing real disk physics. The models use inconsistent computational domains and disk surface density profiles, and the MHD model is isothermal, so the discriminant power may be over- or under-estimated relative to real disks with self-consistent thermal structure.
  • If the MHD model's high density (two orders of magnitude above other models) is an artifact of the semi-analytic approach rather than a physical prediction, the recombination line fluxes for magnetically driven winds could be significantly lower in reality, making detection harder than simulated.
  • The stacking strategy assumes all twelve Band 5b recombination lines originate from the same spatial region; if real disks have more complex ionization structure than the models, stacking may not improve SNR as predicted.
  • Radio frequency interference from satellite mega-constellations in the 10.7–12.7 GHz range removes several lines from the stacking analysis, and growing RFI could further degrade the effective sensitivity by the time SKA reaches full operation.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

3 major / 7 minor

Summary. This paper presents synthetic SKA-Mid (AA4) observations of free-free continuum and hydrogen radio recombination lines (RRLs) arising from photoevaporative (PE), magneto-thermal (MT), and MHD disk wind models. The authors post-process existing simulations with mocassin (for free-free) and ProDiMo (for Hα) and use the official SKA sensitivity calculator to predict detectability at 140 pc. The main claims are: (1) SKA-Mid can spatially resolve free-free emission with ~10 h integration (peak SNR 4–13 depending on band/inclination); (2) stacking 12 Hα lines in Band 5b yields detections for all models with ~10 h integration (peak SNR ≥ 6); and (3) line profiles (FWHM, wing structure) can distinguish PE from magnetically driven winds. The paper is written as a chapter for the 'Advancing Astrophysics with the SKA – II' proceedings.

Significance. The paper provides a timely and useful forecast for SKA capabilities in a scientifically important area—disk wind diagnostics—that is currently poorly constrained observationally. The use of established radiative transfer codes (mocassin, ProDiMo) and the official SKA sensitivity calculator lends credibility to the quantitative predictions. The extension of the ProDiMo hydrogen excitation model to n=200 (19,900 transitions) is a concrete technical contribution. The stacking strategy for Band 5b RRLs is a practical and falsifiable observational proposal. The comparison of multiple wind models (PE, MT, MHD) within a single synthetic-observational framework is valuable for the community, even given the model inhomogeneities discussed below.

major comments (3)
  1. Section 4.1.2 and Figure 4: The central claim that SKA can distinguish PE from MHD winds via line-profile FWHM is heavily dependent on the MHD_B4 model, which has n_H ≈ 4–8×10^8 cm^-3, roughly 100× higher than all other models (n_H ≈ 5×10^6 cm^-3). The authors state this 'huge difference is likely a consequence of the different modeling approaches.' The MHD model (Lesur 2021) is isothermal and independent of stellar properties, meaning the thermal structure that determines ionization (and thus free-free and Hα emissivity) is not self-consistently computed. If the isothermal assumption overestimates the wind density, the MHD_B4 fluxes (SNR=31) and its broad, distinct line wings would be substantially reduced. The paper should more explicitly quantify or bound this sensitivity: e.g., by how much would the MHD_B4 density need to decrease before its stacked Hα SNR falls below the detection阈值
  2. Section 4.1.2, Figure 4 (right panel), and Section 7: At i=40°, the PE and MHD_B6 line profiles become nearly indistinguishable, and the PE model actually shows a broader FWHM than MT_B4. The text acknowledges that 'identifying the dominant launching mechanism will be challenging' at moderate inclinations. However, the Summary (Section 7) presents line-width discrimination as a key finding without this caveat. The summary should be revised to reflect that the distinguishing power is strongly inclination-dependent and is most robust only for the face-on case (which is the least typical geometry).
  3. Section 4.1.1: The models use different computational domains (MT: 0.5–15 au; PE/MHD: 0.3–60 au) and different surface density profiles (MHD has a shallower profile). The authors note this 'somewhat limits a direct comparison.' However, the inner radius difference (0.5 au vs. 0.3 au) is particularly relevant for the MHD models, where the inner disk edge may be the origin of high-density, high-velocity flow. The text itself notes (Section 4.1.2) that the MT model's larger inner radius 'might have an impact on the line profiles and fluxes' and that line wings 'could be more pronounced in reality.' This is a load-bearing caveat for the line-profile comparison claims and should be more prominently discussed, ideally with a brief estimate of how the 0.5 au inner boundary affects the MT model's predicted FWHM relative to the MHD models.
minor comments (7)
  1. Section 4.2: The text states 'in one hour we can detect free-free with a SNR of 5' but the preceding discussion focuses on 10 h and 100 h integrations. It would help to clarify which band, model, and inclination this 1-hour SNR=5 refers to.
  2. Figure 5: The y-axis label 'peak line flux [Jy]' spans 10^2 to 10^6, which seems unusually large for a protoplanetary disk at 140 pc. Please verify the units (should these be μJy or mJy?).
  3. Section 4.2: The RFI exclusion range (10.7–12.7 GHz) is mentioned but the number of surviving lines used for stacking (stated as 12) should be cross-checked against the total number of Hα lines in Band 5b shown in Figure 5.
  4. Figure 7: The y-axis label 'Flux (μJy/beam)' appears to have a formatting issue (the μ symbol renders as a box in some readers). Please verify the encoding.
  5. Section 4.1.2: The accretion luminosity is quoted as L_accr ≈ 0.3 L_☉ in the figure caption for Figure 2, but Section 4.1.1 states L_accr = 2.6×10^-2 L_☉ for the free-free models. Please clarify which value applies to which set of models.
  6. Section 6.2: The GRAVITY+ synergy section focuses almost entirely on massive YSOs (MYSOs), while the rest of the paper concerns classical T Tauri stars. A brief statement on whether GRAVITY+ can also access T Tauri systems would improve coherence.
  7. The paper would benefit from a concise table summarizing all model parameters (domain, surface density profile, L_accr, L_X, β, code used) to help the reader track the differences across models.

Simulated Author's Rebuttal

3 responses · 1 unresolved

We thank the referee for a careful and constructive report. The referee raises three major comments, all of which concern the robustness of our line-profile discrimination between PE and MHD winds. We agree that these caveats deserve more prominent treatment and will revise the manuscript accordingly. Two of the three comments can be fully addressed through revised text and a quantitative estimate; for the third, we can provide a bounding argument but cannot fully resolve the underlying model inhomogeneity without new simulations that are beyond the scope of this proceedings contribution.

read point-by-point responses

  1. Referee: Section 4.1.2 and Figure 4: The central claim that SKA can distinguish PE from MHD winds via line-profile FWHM is heavily dependent on the MHD_B4 model, which has n_H roughly 100x higher than all other models. The isothermal assumption may overestimate the wind density. The paper should quantify or bound this sensitivity: e.g., by how much would the MHD_B4 density need to decrease before its stacked Hα SNR falls below detection threshold?

    Authors: The referee is correct that the MHD_B4 model's high density (n_H ≈ 4–8×10^8 cm^-3) is the primary driver of its high stacked Hα SNR (31), and that this density is a consequence of the isothermal assumption in the Lesur (2021) model, which does not self-consistently compute the thermal structure. We agree that this sensitivity should be quantified. We can provide a bounding estimate as follows. The stacked Hα peak flux scales approximately linearly with the emission measure, i.e., as n_e^2 × V (for optically thin emission) or roughly as n_e × V (for optically thick emission). The Hα emitting region in MHD_B4 is compact and partially optically thick, so the scaling is intermediate. Taking the conservative (optically thin) case, the SNR scales as n_H^2. The detection threshold is SNR ≈ 6, so the MHD_B4 density would need to decrease by a factor of sqrt(31/6) ≈ 2.3 for the stacked SNR to fall to the detection threshold. In the optically thick limit, the scaling is linear in n_H, giving a required decrease factor of 31/6 ≈ 5.2. Thus, the MHD_B4 density would need to decrease by a factor of roughly 2–5 (depending on optical depth regime) before its stacked Hα detection becomes marginal. We note that even a factor of 5 reduction would still leave n_H ≈ 10^8 cm^-3, well above the other models, and the broad line wings (driven by the wind velocity structure, not density) would be unaffected. We will add this quantitative bounding argument to Section 4.1.2 and explicitly state that the MHD_B4 flux predictions carry a systematic uncertainty tied to the isothermal assumption. We will also add a sentence noting that the line-profile FWHM distinction between PE and magnetically driven winds is driven by the wind velocity field, which is a more robust prediction of the MHD launching机制 revision: partial

  2. Referee: Section 4.1.2, Figure 4 (right panel), and Section 7: At i=40°, the PE and MHD_B6 line profiles become nearly indistinguishable, and the PE model actually shows a broader FWHM than MT_B4. The Summary presents line-width discrimination as a key finding without this caveat. The summary should be revised to reflect that the distinguishing power is strongly inclination-dependent and is most robust only for the face-on case.

    Authors: We fully agree. The body text (Section 4.1.2) already acknowledges that 'identifying the dominant launching mechanism will be challenging' at moderate inclinations and that Keplerian broadening washes out the wind-velocity differences. However, the Summary (Section 7) does not carry this caveat and presents line-width discrimination as a general finding. This is an oversight. We will revise the Summary to explicitly state that the line-profile discrimination between PE and magnetically driven winds is most robust for face-on or near-face-on inclinations, and that at moderate inclinations (i ≳ 40°) Keplerian broadening reduces the distinguishing power, though spectral features such as the shoulder at ±20 km/s in the MHD_B6 profile may still provide diagnostic information if the SNR is sufficient. revision: yes

  3. Referee: Section 4.1.1: The models use different computational domains (MT: 0.5–15 au; PE/MHD: 0.3–60 au) and different surface density profiles. The inner radius difference (0.5 au vs. 0.3 au) is particularly relevant for the MHD models, where the inner disk edge may be the origin of high-density, high-velocity flow. This caveat should be more prominently discussed, ideally with a brief estimate of how the 0.5 au inner boundary affects the MT model's predicted FWHM relative to the MHD models.

    Authors: The referee correctly identifies the inner radius difference as a load-bearing caveat for the line-profile comparison. The text already notes that the MT model's larger inner radius 'might have an impact on the line profiles and fluxes' and that line wings 'could be more pronounced in reality,' but we agree this deserves more prominent treatment and at least a rough quantitative estimate. We can provide the following: the MHD_B4 model's FWHM of ≈110 km/s is dominated by the high-velocity flow launched from the innermost disk region (r < 1 au), where the Keplerian velocity is v_K ≈ 30 km/s at 1 au and increases as r^-1/2. At 0.3 au, v_K ≈ 55 km/s; at 0.5 au, v_K ≈ 42 km/s. The wind velocity in MHD models is typically a fraction of the local Keplerian speed, so the inner boundary at 0.5 au (MT) vs. 0.3 au (MHD) implies a difference in maximum launch velocity of roughly 30%. If the MT model's inner radius were extended from 0.5 au to 0.3 au, we would expect the high-velocity wings to be more pronounced, potentially increasing the FWHM by on the order of 10–20 km/s. This would not close the gap with MHD_B4 (FWHM ≈ 110 km/s vs. MT_B4 ≈ 40 km/s face-on), but it could make the MT_B4 profile more similar to the MHD_B6 profile. We will add this estimate to Section 4.1.1 and move the caveat to a more prominent position, making clear that the MT model's FWHM should be considered a lower bound. We cannot, however, fully resolve this issue without rerunning the MT simulations with a smaller inner radius, which is beyond the scope of this proceedings paper. revision: partial

standing simulated objections not resolved
  • The MHD_B4 model's density structure is a direct output of the isothermal Lesur (2021) model and cannot be self-consistently improved without new MHD simulations that include thermal physics. We can bound the sensitivity (as described above) but cannot eliminate the systematic uncertainty within this paper.

Circularity Check

0 steps flagged

No significant circularity found; the paper is a forward-modeling study from simulations to synthetic SKA observations.

full rationale

The paper's derivation chain is straightforward forward modeling: (1) existing wind simulation models (PE, MT, MHD) from the literature are taken as inputs, (2) post-processed with mocassin for free-free emission and ProDiMo for Hα lines, (3) SKA sensitivity calculator provides independent noise estimates, and (4) synthetic observations are generated by adding Gaussian noise to the model sky brightness. No step reduces to its inputs by construction. The self-citations (Weber et al. 2020, 2024, 2025; Ercolano et al. 2021, 2022; Picogna et al. 2019, 2021) reference simulation tools and models that are independently published and externally falsifiable; they are not fitted empirical constants being repackaged as predictions. The paper extends ProDiMo's H model to n=200 (a genuine new computation), and the SNR/detectability claims are derived from the model physics through radiative transfer, not fitted to observational data and then predicted back. The authors transparently acknowledge that the MHD model's higher density is likely a modeling artifact (Section 4.1.2: 'This huge difference is likely a consequence of the different modeling approaches'), which is a correctness concern, not a circularity concern. The only minor issue is that the post-processing pipeline (mocassin/ProDiMo applied to wind models) is largely from co-authors' prior work, but this is standard practice in computational astrophysics and does not make the predictions circular.

Axiom & Free-Parameter Ledger

5 free parameters · 4 axioms · 0 invented entities

The paper does not invent new physical entities, particles, or forces. It uses established simulation codes and wind models. The free parameters are standard stellar/disk parameters chosen to represent a typical T Tauri system, not fitted to reproduce specific observations. The main axioms concern the adequacy of the wind models and the assumption that thermal emission dominates at the targeted wavelengths.

free parameters (5)
  • L_accr (accretion luminosity) = 2.6e-2 L_sun (primary); ~0.3 L_sun (MT models); ~1e-2 L_sun (MT_HD_LA)
    Chosen to represent accretion emission; varied across models to test UV sensitivity of RRLs. Not fitted to data but chosen as representative values.
  • L_X (X-ray luminosity) = 2e30 erg/s
    Fixed to represent a typical T Tauri star. Standard choice from Ercolano et al. (2009).
  • beta (thermal-to-magnetic pressure ratio) = 1e4 (B4 models) and 1e6 (B6 model)
    Chosen to span a range of magnetic field strengths. Not fitted to data.
  • Distance = 140 pc
    Fixed to represent nearby star-forming regions. Standard assumption.
  • Inclinations = [0, 20, 40, 60, 80] degrees
    Sampled to cover viewing angle space. Not fitted.
axioms (4)
  • domain assumption The wind models (PE, MT, MHD) adequately represent the density, velocity, and temperature structure of real protoplanetary disk winds.
    The entire prediction pipeline depends on this. The models use different codes with different physics and are not self-consistently compared (Section 4.1.1).
  • domain assumption Free-free emission and hydrogen recombination lines are the dominant ionized gas tracers at cm wavelengths.
    Section 3 discusses other mechanisms (gyrosynchrotron, AME) but the simulations only model free-free and RRLs. Contamination from non-thermal processes is acknowledged but not included in the synthetic observations.
  • domain assumption The SKA-Mid AA4 performance specifications used in the sensitivity calculator will be achieved in operations.
    Predictions depend on the assumed sensitivity and beam parameters of the future SKA-Mid AA4 configuration.
  • domain assumption Stacking multiple RRLs from the same wind region is physically justified.
    Section 4.2 states this is justified because simulations indicate the lines originate from the same region. This is tested within the models but not observationally verified.

pith-pipeline@v1.1.0-glm · 28631 in / 3269 out tokens · 394029 ms · 2026-07-09T06:34:11.154517+00:00 · methodology

0 comments
read the original abstract

Protoplanetary disks represent a crucial stage in the evolution of Young Stellar Objects towards the formation of fully formed planetary systems. While substantial progress has been made in the last decades in the characterization of the dust and molecular gas in these systems, the ionized component remains poorly understood. Ionized gas traces important processes such as photoevaporation, accretion, disk winds, and jets, and therefore is key to studying disk dynamics, evolution, and ultimately planet formation. In this paper, we investigate the capabilities of the forthcoming SKA telescope to probe this component in protoplanetary disks within nearby star forming regions. We present state-of-the-art simulations of photoevaporative, magneto-thermal, and magnetohydrodynamic winds, and generate theoretical predictions and synthetic SKAO observations to assess its potential in detecting and characterizing free-free emission and Hydrogen recombination lines. Finally, we discuss synergies with complementary facilities and how they will provide a comprehensive, multi-scale view of disk winds and offer critical insights on the mechanisms driving disk evolution and the onset of planet formation.

Figures

Figures reproduced from arXiv: 2607.07571 by Antonio Garufi, Asmita Bhandare, Barbara Ercolano, Christian Rab, Claudia Toci, Claudio Codella, Elena Viscardi, Eleonora Bianchi, Enrique Mac\'ias, Evgenia Koumpia, Francesca Bacciotti, Geoffroy Lesur, Giovanni Sabatini, Greta Guidi, Izaskun Jim\'enez-Serra, John D. Ilee, Leonardo Testi, Linda Podio, Luca Cacciapuoti, Michael L. Weber, Tyler Bourke, Vincent Pi\'etu, Yinhao Wu.

Figure 1
Figure 1. Figure 1: Schematic representation of a protoplanetary disk highlighting accretion and ejection processes. The spatial scales at the bottom are indicative only and serve to illustrate the approximate emitting regions of the different components. In this paper we investigate the capabilities of SKA AA4 (Braun et al., 2019) in unveiling ionized gas tracers in disks. We outline the key science questions that can be add… view at source ↗
Figure 2
Figure 2. Figure 2: Two-dimensional density structure (total hydrogen number density), wind velocity field, and main line emitting regions (boxes), with the neutral hydrogen number density in the background. The dashed white lines in the left panels mark the contour levels indicated in the colourbar. The white solid lines in the middle and right panels indicate a visual extinction of unity. The top row shows the MT_HD wind mo… view at source ↗
Figure 3
Figure 3. Figure 3: Same as [PITH_FULL_IMAGE:figures/full_fig_p012_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Stacked and peak normalised H𝛼 line profiles for the various models. The left panel shows the profiles for the disk seen face-on, the right panel shows the profiles for an inclination of 𝑖 = 40◦ (right panel). Please note that in the left panel, the model MT_HD (orange line) is barely visible, as it is almost identical with the MT_HD_LA (green line) model. further emission properties by means of the modell… view at source ↗
Figure 5
Figure 5. Figure 5: Predicted peak line fluxes for the H𝛼 for all the here presented models at a distance of 140 pc, inclination of 𝑖 = 40◦ and a bandwidth of 1 km/s. On the left side of the panel, the stacked peak fluxes are shown (simply adding all the detectable lines). The horizontal grey solid and dashed lines indicate the detection limits, in terms of image rms, for integration times of 10 h and 100 h, respectively. The… view at source ↗
Figure 6
Figure 6. Figure 6: Left column: simulation of free–free emission with the MT_B4 model at 2.5 cm, for a disk with an inclination of 0° (top) and 90° (bottom). Middle and right panels: simulated observations for 10h integration time with SKA-Mid AA4 at Band 5a and 5b, using briggs weighting with robust = -2. The resulting beams are 0. ′′03 × 0. ′′02 and 0. ′′05 × 0. ′′04, respectively. antennas with a 15 m diameter, to obtain … view at source ↗
Figure 7
Figure 7. Figure 7: Radial profile along the horizontal direction of the free–free emission from simulations of SKA observations with 10 hours integration time and briggs weighting with a robust of -2, from the MT_B4 (see [PITH_FULL_IMAGE:figures/full_fig_p016_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Spectral Energy Distribution of the free–free emission from the magneto-thermal model (orange circles) and the photoevaporative model (blue circle). The solid lines show the interpolated power-laws between the flux and the frequency (similarly for the dashed lines, computed using the models with inclination of 90°). Shaded blue areas show the frequencies covered by SKA-Mid band 5. of 0.25 km/s and a robust… view at source ↗
Figure 9
Figure 9. Figure 9: Spatially integrated spectra of the 12 stacked H𝛼 lines from the PE model and the MHD_B6 model, for disk inclinations of 0° and 80°. The cubes have been obtained by assuming an integration time of 10 hours and using robust 2 parameter with 0. ′′024 tapering and a spectral resolution of 1km/s. in continuum sensitivity will be slightly smaller, since MerKAT band 5b is expected to provide a 2.5 GHz bandwidth,… view at source ↗

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